Considering that the effect of different types of energy on sustainable development differs, the optimization of energy structure is commonly seen as a decisive factor for sustainable development. In this study, we focus on energy structure and construct a dynamic stochastic general equilibrium (DSGE) analysis framework including the environment, society, and the economy. Furthermore, we analyze the effect of different technology shocks on sustainable development when the proportion of clean energy is separately set at 10%, 20%, and 40%. To demonstrate the conclusions of the DSGE analysis framework, we construct the sustainability index and measure the relationship between the sustainability index scores and the proportion of clean energy of 68 countries in 2017, and the ${\mathrm{R}}^2$ of the linear relationship between the sustainability index score and the proportion of clean energy was 0.30. Results show that the technology shock of clean energy exhibits more benefits for sustainable development than that of non-clean energy. Moreover, we find that the optimization of the energy structure can be helpful for the enhancement of sustainable development capacity. This study is helpful to expand the DSGE analysis framework from the perspective of energy structure. This study also provides effective ways and reference suggestions for local governments to optimize energy structure and improve sustainable development capability.

From the perspective of spatial interaction, the impact of the modern service industry’s agglomeration on today’s increasingly connected cities is worth studying. This study uses a spatial econometric model to test the development trends and factors influencing the modern service industry’s agglomeration in the Yangtze River Delta city group. The results show that the industry has the highest agglomeration in leasing and business and the lowest in education. The overall concentration of the industry is generally low, implying a more fragmented distribution. Moreover, the agglomeration has a significant positive spatial correlation with economic development, knowledge intensity, and city size. However, it has a negative correlation with information technology level and transportation infrastructure, inconsistent with existing research. This study argues that the development of the information technology level and transportation infrastructure in a city could lead to the ‘virtual agglomeration’ of the modern service industry and gradual decentralisation in geographical distribution. This is a new paradox that city groups may face when improving their infrastructure and developing modern services. This study uses the spatial interaction perspective to propose policy recommendations for promoting the modern service industry’s agglomeration and coordinated regional development.

This paper theoretically analyses the mechanism of the ratchet effect of land finance and adaptive expectations on residential land prices and discuss the distort factors and spatial characteristics of residential land price in the Yangtze River Delta urban agglomeration (YRDUA) from 2008 to 2018. It is found that:(1) Land finance and adaptive expectations significantly drive the long-term growth of residential land prices and maintain the ratchet effect under the interaction. (2) There are significant spatial spillover benefits of residential land prices, and land finance and adaptive expectations not only drive the increase of local residential land prices but also have significant positive benefits on residential land prices in neighbouring areas. (3) Land price distortion is significant in municipalities directly under the central government and provincial capitals. However, residential land prices in cities farther away from large cities are lower than their reasonable values, and the distortion correction coefficient shows a spatially graded distribution spreading from large cities to the periphery. Land finance and adaptive expectations do not make residential land prices in all cities higher than their reasonable values. The above findings have some theoretical and policy implications for optimizing land administration.